Enrique Querol

4.7k citations
155 papers · 3.9k · h-index 32

Impact in

Papers in

    • Protein Structure and Dynamics 38
    • RNA and protein synthesis mechanisms 18
    • Machine Learning in Bioinformatics 16
    • Microbial infections and disease research 25

Enrique Querol

150 papers receiving 3.8k citations

Peers

Enrique Querol
Comparison fields: 5 of 123
  • Microbiology 594
  • Biotechnology 513
  • Molecular Biology 2.5k
  • Hematology 178
  • Parasitology 88
Replace Muriel Delepierre with:
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Enrique Querol relative to Muriel Delepierre France Muriel Delepierre's profile →
Citations per field
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Muriel Delepierre · 1×
Citations per year

Countries citing papers authored by Enrique Querol

Since Specialization
Citations

This map shows the geographic impact of Enrique Querol's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Enrique Querol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Enrique Querol more than expected).

Fields of papers citing papers by Enrique Querol

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Enrique Querol. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Enrique Querol. The network helps show where Enrique Querol may publish in the future.

Co-authors

The 25 scholars most cited alongside Enrique Querol, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Enrique Querol Line = papers co-authored together Enrique Querol links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 155 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997363
2 1996217
3 2001209
4 1997181
5 2000135
6 1994109
7 200678
8 199573
9 199871
10 199266
11 199164
12 201055
13 199555
14 201354
15 200653
16 201746
17 199846
18 200145
19 199645
20 199643

About Enrique Querol

Enrique Querol is a scholar working on Molecular Biology, Microbiology, Materials Chemistry, Biotechnology and Oncology, having authored 155 papers that have together received 3.9k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (38 papers), Microbial infections and disease research (25 papers), Enzyme Structure and Function (22 papers), RNA and protein synthesis mechanisms (18 papers), Enzyme Production and Characterization (18 papers), Machine Learning in Bioinformatics (16 papers), Microbial Metabolites in Food Biotechnology (12 papers) and Bacteriophages and microbial interactions (12 papers). The work is most often cited by research in Microbiology (594 citations), Biotechnology (513 citations), Molecular Biology (2.5k citations), Hematology (178 citations) and Parasitology (88 citations). Enrique Querol has collaborated with scholars based in Spain, United Kingdom and Germany. Frequent co-authors include Francesc Avilés, Josep A. Pérez-Pons, Juan Cedano, Jaume Piñol, Patrick Aloy, Michael J.E. Sternberg, Ángel Mozo-Villarias, Baldomero Oliva, Òscar Q. Pich and Antoni Planas. Their work appears in journals such as Journal of Molecular Biology, Molecular Microbiology, PLoS ONE, Journal of Biological Chemistry and Proteins Structure Function and Bioinformatics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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